Subtraction images are a good means to visualize interval changes between follow-up images. The technique has been applied, for example, to thorax X-ray images. Some studies show that reporting accuracy and speed increase with the use of subtraction images. For example, a non-rigid 2D image registration method is used prior to subtraction of the current image in order to align corresponding anatomical parts. Ideally, the subtraction image should become medium grey except for the places where interval changes have occurred. The most prevalent reason for image artifacts in subtraction images is a difference in patient pose between both acquisitions. In particular, the patient may be rotated in between image acquisitions. For this reason, a technique has been proposed to compensate for a known patient rotation.
The paper “A novel registration method for interval change detection between two chest X-ray images with different rotation angles”, by A. Shimizu et al., in: Acad. Radiol. 2006; 13:503-511, hereinafter: Shimizu, discloses a registration technique in which it is assumed that all the X-ray absorption recorded by an X-ray image has taken place in a coronal plane intersecting the patient. The position of this coronal plane is referred to as the depth of the shadow of interest. With this limitation, a synthetic radiographic image is constructed that compensates the difference in patient pose, and thus eliminates the artifacts which may occur in subtracted images when the anatomic structure is imaged from differing angles. According to Shimizu et al., when the depth of the shadow of interest is known from another clinical examination, such as tomography, a subtraction image is computed by registering the two images, based on the known patient rotation and known depth of the shadow of interest, and the interval change of the shadow is examined on the subtraction image. If the depth is unknown or interval changes are detected at different depths, the depth is continuously varied and a series of the subtraction images are constructed and interpreted. To this end, the clinical user observes a sequence of subtraction images with changing depth parameter.